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CSpritz: accurate prediction of protein disorder segments with annotation for homology, secondary structure and linear motifs

Ian Walsh, Alberto J. M. Martin, Tomàs Di Domenico, Alessandro Vullo, Gianluca Pollastri, Silvio C. E. Tosatto
2011 Nucleic Acids Research  
As a novel feature, CSpritz provides information about structural homologues as well as secondary structure and short functional linear motifs in each disordered segment.  ...  CSpritz is a web server for the prediction of intrinsic protein disorder. It is a combination of previous Spritz with two novel orthogonal systems developed by our group (Punch and ESpritz).  ...  ACKNOWLEDGEMENTS The authors are grateful to members of the BioComputing UP lab for insightful discussions.  ... 
doi:10.1093/nar/gkr411 pmid:21646342 pmcid:PMC3125791 fatcat:5fz3tyccbbg6rj5hnhg52ktv3m

An Overview of Predictors for Intrinsically Disordered Proteins over 2010–2014

Jianzong Li, Yu Feng, Xiaoyun Wang, Jing Li, Wen Liu, Li Rong, Jinku Bao
2015 International Journal of Molecular Sciences  
The sequence-structure-function paradigm of proteins has been changed by the occurrence of intrinsically disordered proteins (IDPs).  ...  We analyzed the algorithms used for IDPs prediction by these tools and we also discussed the basic concept of various prediction methods for IDPs.  ...  Jianzong Li, Wen Liu and Li Rong wrote and revised this manuscript. Jinku Bao took responsibility for reviewing the manuscript. Conflicts of Interest The authors declare no conflict of interest.  ... 
doi:10.3390/ijms161023446 pmid:26426014 pmcid:PMC4632708 fatcat:zidnpfwb2jhrpgqoezjjsd6qhq

How disordered is my protein and what is its disorder for? A guide through the "dark side" of the protein universe

Philippe Lieutaud, François Ferron, Alexey V. Uversky, Lukasz Kurgan, Vladimir N. Uversky, Sonia Longhi
2016 Intrinsically Disordered Proteins  
The identification of disordered regions facilitates the functional annotation of proteins and is instrumental for delineating boundaries of protein domains amenable to structural determination with X-ray  ...  This article discusses a comprehensive selection of databases and methods currently employed to disseminate experimental and putative annotations of disorder, predict disorder and identify regions involved  ...  [86] [87] [88] [89] [90] [91] Two models complementary to MoRF-like interactions, the Short Linear Motif (SLiM) and the Eukaryotic Linear Motif (ELM), are based on sequence motifs that are recognized  ... 
doi:10.1080/21690707.2016.1259708 pmid:28232901 pmcid:PMC5314888 fatcat:zetixzpkyvhntjv4pkwmrfu5ee

Single-cell transcriptomics to define Plasmodium falciparum stage-transition in the mosquito midgut [article]

Mubasher Mohammed, Alexis Dziedziech, Vaishnovi Sekar, Medard Ernest, Thiago Luiz Alves E Silva, Balu Balan, S. Noushin Emami, Inna Biryukova, Marc R. Friedländer, Aaron Jex, Marcelo Jacobs Lorena, Johan Henriksson (+2 others)
2022 bioRxiv   pre-print
Further, employing structure-based functional predictions we found several upregulated genes predicted to encode intrinsically disordered proteins (IDPs), a category of proteins known for their importance  ...  in regulation of transcription, translation and protein-protein interactions.  ...  Acknowledgment We would like to thank The Microbial Single Cell Genomics (MSCG) facility, SciLifeLab, for assistance with the single-cell sorting and optimization of molecular workflows and library preparations  ... 
doi:10.1101/2022.04.05.487115 fatcat:pkq76646bvhwjknl2hyonarwbe

Orders of disorder: computational analysis of the interactions of intrinsically disordered proteins

Erzsébet Fichó, Bálint Mészáros
DIBS: a repository of disordered binding sites mediating interactions with ordered proteins.  ...  under the guidance of Prof. István Simon and the supervision of Dr. Bálint Mészáros.  ...  Prediction of disordered binding regions Interacting linear motifs are usually short and evolutionarily variable segments, which in most cases, fall into locally disordered regions [36] .  ... 
doi:10.15476/elte.2018.256 fatcat:dexyhyzkybedtmu25t4ub2ig2a